A 3D imager uses a triangulation method to measure the 3D coordinates of points on an object. The 3D imager usually includes a projector that projects onto a surface of the object either a pattern of light in a line or a pattern of light covering an area. A camera is coupled to the projector in a fixed relationship, for example, by attaching a camera and the projector to a common frame. The light emitted from the projector is reflected off of the object surface and detected by the camera. Since the camera and projector are arranged in a fixed relationship, the distance to the object may be determined using trigonometric principles. Compared to coordinate measurement devices that use tactile probes, triangulation systems provide advantages in quickly acquiring coordinate data over a large area. As used herein, the resulting collection of 3D coordinate values or data points of the object being measured by the triangulation system is referred to as point cloud data or simply a point cloud.
A 3D imager may be attached to a variety of mover devices such as robotic devices and aerial drones. A method known as videogrammetry provides a way to register multiple 3D data sets when there is relative motion between the 3D imager and an object being measured. Videogrammetry can further be used to provide data needed to directly determine 3D coordinates when multiple two-dimensional (2D) images with the camera at different positions relative to the object being measured. In this case, videogrammetry is further making use of triangulation principles. Hence the term videogrammetry as used herein is understood to further encompass triangulation.
A particular issue that may be encountered when using triangulation (which may further include videogrammetry) is lack of accuracy and detail when distances from a 3D imager to an object are large or variable. Accordingly, while existing triangulation-based 3D imager devices are suitable for their intended purpose, the need for improvement remains.